3 Estimation of a Network with Evolutionary Computation
If the specification of the neural network for approximation appears to be inspired by biology, the reader will no doubt suspect that the best way to estimate or train a network is inspired by genetics and evolution. Estimating a nonlinear model is always tricky business. The programs may fail to converge, or they may converge to locally, rather than globally, optimal estimates. We show that the best way to estimate a network, to implement the network, is to harness the power of evolutionary genetic search algorithms.
3.1 Data Preprocessing
Before moving to the actual estimation, however, the first order of business is to adjust or scale the data and to remove nonstationarity. In other ...
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